E18 mouse brain, short read profiling
29 mars 2019
Contents
1 Cellranger Illumina profiling (190c)
## [1] 27998 190## [1] 27998 186
## [1] 2000
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
##
## Number of nodes: 186
## Number of edges: 4045
##
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.7919
## Number of communities: 4
## Elapsed time: 0 seconds
2 Cellranger Illumina profiling (951c)
## [1] 27998 951## [1] 27998 935
## [1] 2000
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
##
## Number of nodes: 935
## Number of edges: 25447
##
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.8540
## Number of communities: 9
## Elapsed time: 0 seconds
3 Adding Nanopore data (ISOG/ISO)
4 Integration RNA
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
##
## Number of nodes: 1121
## Number of edges: 31187
##
## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.8374
## Number of communities: 10
## Elapsed time: 0 seconds
5 Gene Markers Heatmap
6 Clusters re-labelling, saving .rds file
7 Gene markers
8 Heatmap
#Session Info
sessionInfo()## R version 3.5.2 (2018-12-20)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux buster/sid
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.5.so
##
## locale:
## [1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8
## [5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=fr_FR.UTF-8
## [7] LC_PAPER=fr_FR.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] bindrcpp_0.2.2 metap_1.1 cowplot_0.9.4
## [4] ggrepel_0.8.0 xtable_1.8-3 knitr_1.21
## [7] RColorBrewer_1.1-2 forcats_0.4.0 stringr_1.3.1
## [10] purrr_0.3.0 readr_1.3.1 tidyr_0.8.2
## [13] tibble_2.0.1 ggplot2_3.1.0 tidyverse_1.2.1
## [16] pheatmap_1.0.12 dplyr_0.7.8 Seurat_3.0.0.9000
## [19] BiocStyle_2.10.0
##
## loaded via a namespace (and not attached):
## [1] tsne_0.1-3 nlme_3.1-137 bitops_1.0-6
## [4] lubridate_1.7.4 httr_1.4.0 backports_1.1.3
## [7] tools_3.5.2 R6_2.3.0 irlba_2.3.3
## [10] KernSmooth_2.23-15 lazyeval_0.2.1 colorspace_1.4-0
## [13] withr_2.1.2 npsurv_0.4-0 tidyselect_0.2.5
## [16] compiler_3.5.2 cli_1.0.1 rvest_0.3.2
## [19] xml2_1.2.0 plotly_4.8.0 labeling_0.3
## [22] bookdown_0.9 caTools_1.17.1.1 scales_1.0.0
## [25] lmtest_0.9-36 ggridges_0.5.1 pbapply_1.4-0
## [28] digest_0.6.18 rmarkdown_1.11 R.utils_2.8.0
## [31] pkgconfig_2.0.2 htmltools_0.3.6 bibtex_0.4.2
## [34] readxl_1.3.1 htmlwidgets_1.3 rlang_0.3.1
## [37] rstudioapi_0.10 generics_0.0.2 bindr_0.1.1
## [40] zoo_1.8-4 jsonlite_1.6 ica_1.0-2
## [43] gtools_3.8.1 R.oo_1.22.0 magrittr_1.5
## [46] Matrix_1.2-15 Rcpp_1.0.0 munsell_0.5.0
## [49] ape_5.3 reticulate_1.11.1 R.methodsS3_1.7.1
## [52] stringi_1.2.4 yaml_2.2.0 gbRd_0.4-11
## [55] MASS_7.3-51.1 gplots_3.0.1.1 Rtsne_0.15
## [58] plyr_1.8.4 grid_3.5.2 parallel_3.5.2
## [61] gdata_2.18.0 listenv_0.7.0 crayon_1.3.4
## [64] lattice_0.20-38 haven_2.1.0 splines_3.5.2
## [67] hms_0.4.2 SDMTools_1.1-221 pillar_1.3.1
## [70] igraph_1.2.4 future.apply_1.2.0 codetools_0.2-16
## [73] glue_1.3.0 evaluate_0.12 lsei_1.2-0
## [76] modelr_0.1.4 data.table_1.12.0 BiocManager_1.30.4
## [79] png_0.1-7 Rdpack_0.10-1 cellranger_1.1.0
## [82] gtable_0.2.0 RANN_2.6.1 future_1.12.0
## [85] assertthat_0.2.0 xfun_0.4 rsvd_1.0.0
## [88] broom_0.5.1 survival_2.43-3 viridisLite_0.3.0
## [91] cluster_2.0.7-1 globals_0.12.4 fitdistrplus_1.0-14
## [94] ROCR_1.0-7